Baseline NIH stroke scale responses estimate the probability of each particular stroke subtype.
BACKGROUND
Emergency treatment of ischemic stroke should ideally be mechanism specific, but acute subtype diagnosis is problematic. Since different subtypes often are associated with specific patterns of neurological deficits, we hypothesize that scores on baseline NIH stroke scale (NIHSS) items may help emergently stratify patients by their probability of having a particular stroke subtype.


METHODS
We performed multivariate polytomous logistic regression analyses on 1,281 patients enrolled in the Trial of ORG 10172 in Acute Stroke Treatment (TOAST). We tested the predictive value of individual items to the baseline NIHSS exam, and syndromic combinations of those items, in anticipating the TOAST stroke subtype at 3 months adjusting for atrial fibrillation. We then used the most significant NIHSS items to construct a predictive model.


RESULTS
The NIHSS items that discriminate between stroke subtypes are language, neglect, visual field and brachial predominance of weakness. Among patients without atrial fibrillation, a normal score for these 4 variables conveys a 46% chance of lacunar stroke, 12% of atherothrombotic stroke and 10% of cardioembolism. This pattern gradually reverses with increased numbers of abnormal responses. Those with abnormalities in all 4 items have a 0.1% chance of lacunar stroke, 50% of atherothrombotic stroke and 39% of cardioembolism.


CONCLUSIONS
Language, neglect, visual fields and brachial predominance of weakness in the baseline NIHSS help discriminate between subtypes, particularly between lacunar and nonlacunar strokes. Clinical trials testing interventions aimed to particular stroke mechanisms may use these NIHSS items to emergently stratify patients based on their probability of having a particular stroke subtype.
Leira
E C
EC
Department of Neurology, Carver College of Medicine, University of Iowa, Iowa City, Iowa 52242, USA. enrique-leira@uiowa.edu
Adams
H P
HP
Rosenthal
G E
GE
Torner
J C
JC
D001037:Aphasia / Q000209:etiology; D001132:Arm; D001281:Atrial Fibrillation / Q000150:complications; D020520:Brain Infarction / Q000175:diagnosis / Q000453:epidemiology; D002545:Brain Ischemia / Q000175:diagnosis / Q000453:epidemiology; D015331:Cohort Studies; D004311:Double-Blind Method; D006423:Hemianopsia / Q000209:etiology; D006801:Humans; D002537:Intracranial Arteriosclerosis / Q000150:complications; D020766:Intracranial Embolism / Q000175:diagnosis / Q000453:epidemiology; D016015:Logistic Models; D018908:Muscle Weakness / Q000209:etiology; D010291:Paresis / Q000209:etiology; D010468:Perceptual Disorders / Q000209:etiology; D011237:Predictive Value of Tests; D011446:Prospective Studies; D016032:Randomized Controlled Trials as Topic / Q000706:statistics & numerical data; D012306:Risk; D012720:Severity of Illness Index; D020521:Stroke / Q000145:classification* / Q000150:complications / Q000453:epidemiology